Taming quantum systems: A tutorial for using shortcuts-to-adiabaticity, quantum optimal control, and reinforcement learning
This repository contains the Jupyter notebooks accompanying arXiv:2501.16436 Taming quantum systems: A tutorial for using shortcuts-to-adiabaticity, quantum optimal control, and reinforcement learning by Duncan et al., and instructions for using them.
Sec II: Shortcuts to Adiabaticity
- Notebook 2.1:
Sec III: Quantum Optimal Control
- Notebook 3.1:
Sec IV: Reinforcement Learning for Optimal Quantum Control
- Notebook 4.1: Universal single-qubit state preparation
- Notebook 4.2: RL vs. counter-diabatic driving in the presence of Trotterization errors
- Notebook 4.3: Continuous single-qubit feedback control using quantum data
Required packages can be found in requirements.txt.
You may create a virtual environment using pip and install all packages at once by running:
.. python -m venv .ctrl_tutor
.. source .ctrl_tutor/bin/activate
.. python -m pip install --upgrade pip
.. python -m pip install -r requirements.txt
To run the jupyter notebooks, run
.. jupyter lab
and select tje notebook you're interested in.